Hi,
Re-writing the test in the following manner works. But I am not sure if
this is the correct way.
def testAggregationWithNull(): Unit = {
val env = ExecutionEnvironment.getExecutionEnvironment
val dataSet = env.fromElements[(Integer, String)]((123, "a"), (234,
"b"), (345, "c"), (0, "d"))
implicit val rowInfo: TypeInformation[Row] = new RowTypeInfo(
Seq(BasicTypeInfo.INT_TYPE_INFO, BasicTypeInfo.STRING_TYPE_INFO),
Seq("id", "name"))
val rowDataSet = dataSet.map {
entry =>
val row = new Row(2)
val amount = if(entry._1<100) null else entry._1
row.setField(0, amount)
row.setField(1, entry._2)
row
}
val total =
rowDataSet.toTable.select('id.sum).collect().head.productElement(0)
assertEquals(total, 702)
}
On Sun, Jun 14, 2015 at 11:42 PM, Shiti Saxena <ssaxena....@gmail.com>
wrote:
> Hi,
>
> For
>
> val table = env.fromElements[(Integer, String)]((123, "a"), (234, "b"),
> (345, "c"), (null, "d")).toTable
>
> I get the following error,
>
> Error translating node 'Data Source "at
> org.apache.flink.api.scala.ExecutionEnvironment.fromElements(ExecutionEnvironment.scala:505)
> (org.apache.flink.api.java.io.CollectionInputFormat)" : NONE [[
> GlobalProperties [partitioning=RANDOM_PARTITIONED] ]] [[ LocalProperties
> [ordering=null, grouped=null, unique=null] ]]': null
> org.apache.flink.optimizer.CompilerException: Error translating node 'Data
> Source "at
> org.apache.flink.api.scala.ExecutionEnvironment.fromElements(ExecutionEnvironment.scala:505)
> (org.apache.flink.api.java.io.CollectionInputFormat)" : NONE [[
> GlobalProperties [partitioning=RANDOM_PARTITIONED] ]] [[ LocalProperties
> [ordering=null, grouped=null, unique=null] ]]': null
> at
> org.apache.flink.optimizer.plantranslate.JobGraphGenerator.preVisit(JobGraphGenerator.java:360)
> at
> org.apache.flink.optimizer.plantranslate.JobGraphGenerator.preVisit(JobGraphGenerator.java:103)
> at
> org.apache.flink.optimizer.plan.SourcePlanNode.accept(SourcePlanNode.java:87)
> at
> org.apache.flink.optimizer.plan.SingleInputPlanNode.accept(SingleInputPlanNode.java:199)
> at
> org.apache.flink.optimizer.plan.SingleInputPlanNode.accept(SingleInputPlanNode.java:199)
> at
> org.apache.flink.optimizer.plan.SingleInputPlanNode.accept(SingleInputPlanNode.java:199)
> at
> org.apache.flink.optimizer.plan.SingleInputPlanNode.accept(SingleInputPlanNode.java:199)
> at
> org.apache.flink.optimizer.plan.SingleInputPlanNode.accept(SingleInputPlanNode.java:199)
> at
> org.apache.flink.optimizer.plan.SingleInputPlanNode.accept(SingleInputPlanNode.java:199)
> at
> org.apache.flink.optimizer.plan.OptimizedPlan.accept(OptimizedPlan.java:127)
> at
> org.apache.flink.optimizer.plantranslate.JobGraphGenerator.compileJobGraph(JobGraphGenerator.java:170)
> at
> org.apache.flink.test.util.TestEnvironment.execute(TestEnvironment.java:52)
> at
> org.apache.flink.api.java.ExecutionEnvironment.execute(ExecutionEnvironment.java:789)
> at
> org.apache.flink.api.scala.ExecutionEnvironment.execute(ExecutionEnvironment.scala:576)
> at org.apache.flink.api.scala.DataSet.collect(DataSet.scala:544)
> at
> org.apache.flink.api.scala.table.test.AggregationsITCase.testAggregationWithNull(AggregationsITCase.scala:135)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:606)
> at
> org.junit.runners.model.FrameworkMethod$1.runReflectiveCall(FrameworkMethod.java:47)
> at
> org.junit.internal.runners.model.ReflectiveCallable.run(ReflectiveCallable.java:12)
> at
> org.junit.runners.model.FrameworkMethod.invokeExplosively(FrameworkMethod.java:44)
> at
> org.junit.internal.runners.statements.InvokeMethod.evaluate(InvokeMethod.java:17)
> at
> org.junit.internal.runners.statements.RunBefores.evaluate(RunBefores.java:26)
> at
> org.junit.internal.runners.statements.RunAfters.evaluate(RunAfters.java:27)
> at org.junit.rules.ExternalResource$1.evaluate(ExternalResource.java:48)
> at org.junit.rules.RunRules.evaluate(RunRules.java:20)
> at org.junit.runners.ParentRunner.runLeaf(ParentRunner.java:271)
> at
> org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:70)
> at
> org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:50)
> at org.junit.runners.ParentRunner$3.run(ParentRunner.java:238)
> at org.junit.runners.ParentRunner$1.schedule(ParentRunner.java:63)
> at org.junit.runners.ParentRunner.runChildren(ParentRunner.java:236)
> at org.junit.runners.ParentRunner.access$000(ParentRunner.java:53)
> at org.junit.runners.ParentRunner$2.evaluate(ParentRunner.java:229)
> at org.junit.runners.ParentRunner.run(ParentRunner.java:309)
> at org.junit.runners.Suite.runChild(Suite.java:127)
> at org.junit.runners.Suite.runChild(Suite.java:26)
> at org.junit.runners.ParentRunner$3.run(ParentRunner.java:238)
> at org.junit.runners.ParentRunner$1.schedule(ParentRunner.java:63)
> at org.junit.runners.ParentRunner.runChildren(ParentRunner.java:236)
> at org.junit.runners.ParentRunner.access$000(ParentRunner.java:53)
> at org.junit.runners.ParentRunner$2.evaluate(ParentRunner.java:229)
> at
> org.junit.internal.runners.statements.RunBefores.evaluate(RunBefores.java:26)
> at
> org.junit.internal.runners.statements.RunAfters.evaluate(RunAfters.java:27)
> at org.junit.runners.ParentRunner.run(ParentRunner.java:309)
> at org.junit.runner.JUnitCore.run(JUnitCore.java:160)
> at
> com.intellij.junit4.JUnit4IdeaTestRunner.startRunnerWithArgs(JUnit4IdeaTestRunner.java:78)
> at
> com.intellij.rt.execution.junit.JUnitStarter.prepareStreamsAndStart(JUnitStarter.java:212)
> at com.intellij.rt.execution.junit.JUnitStarter.main(JUnitStarter.java:68)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:606)
> at com.intellij.rt.execution.application.AppMain.main(AppMain.java:140)
> Caused by: java.lang.NullPointerException
> at
> org.apache.flink.api.common.typeutils.base.IntSerializer.serialize(IntSerializer.java:63)
> at
> org.apache.flink.api.common.typeutils.base.IntSerializer.serialize(IntSerializer.java:27)
> at
> org.apache.flink.api.scala.typeutils.CaseClassSerializer.serialize(CaseClassSerializer.scala:89)
> at
> org.apache.flink.api.scala.typeutils.CaseClassSerializer.serialize(CaseClassSerializer.scala:29)
> at
> org.apache.flink.api.java.io.CollectionInputFormat.writeObject(CollectionInputFormat.java:88)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:606)
> at java.io.ObjectStreamClass.invokeWriteObject(ObjectStreamClass.java:988)
> at java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1493)
> at
> java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1429)
> at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1175)
> at
> java.io.ObjectOutputStream.defaultWriteFields(ObjectOutputStream.java:1541)
> at java.io.ObjectOutputStream.writeSerialData(ObjectOutputStream.java:1506)
> at
> java.io.ObjectOutputStream.writeOrdinaryObject(ObjectOutputStream.java:1429)
> at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1175)
> at java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:347)
> at
> org.apache.flink.util.InstantiationUtil.serializeObject(InstantiationUtil.java:314)
> at
> org.apache.flink.util.InstantiationUtil.writeObjectToConfig(InstantiationUtil.java:268)
> at
> org.apache.flink.runtime.operators.util.TaskConfig.setStubWrapper(TaskConfig.java:273)
> at
> org.apache.flink.optimizer.plantranslate.JobGraphGenerator.createDataSourceVertex(JobGraphGenerator.java:853)
> at
> org.apache.flink.optimizer.plantranslate.JobGraphGenerator.preVisit(JobGraphGenerator.java:260)
> ... 55 more
>
>
> Does this mean that the collect method is being called before doing the
> aggregation? Is this because base serializers do not handle null values
> like POJOSerializer? And is that why fromCollection does not support
> collections with null values?
>
> Or I could write the test using a file load if thats alright.
>
>
> On Sun, Jun 14, 2015 at 11:11 PM, Aljoscha Krettek <aljos...@apache.org>
> wrote:
>
>> Hi,
>> sorry, my mail client sent before I was done.
>>
>> I think the problem is that the Scala compiler derives a wrong type for
>> this statement:
>> val table = env.fromElements((123, "a"), (234, "b"), (345, "c"), (null,
>> "d")).toTable
>>
>> Because of the null value it derives (Any, String) as the type if you do
>> it like this, I think it should work:
>> val table = env.fromElements[(Integer, String)]((123, "a"), (234, "b"),
>> (345, "c"), (null, "d")).toTable
>>
>> I used Integer instead of Int because Scala will complain that null is
>> not a valid value for Int otherwise.
>>
>> Cheers,
>> Aljoscha
>>
>>
>> On Sun, 14 Jun 2015 at 19:34 Aljoscha Krettek <aljos...@apache.org>
>> wrote:
>>
>>> Hi,
>>> I think the problem is that the Scala compiler derives a wrong type for
>>> this statement:
>>>
>>>
>>>
>>> On Sun, 14 Jun 2015 at 18:28 Shiti Saxena <ssaxena....@gmail.com> wrote:
>>>
>>>> Hi Aljoscha,
>>>>
>>>> I created the issue FLINK-2210
>>>> <https://issues.apache.org/jira/browse/FLINK-2210> for aggregate on
>>>> null. I made changes to ExpressionAggregateFunction to handle ignore null
>>>> values. But I am unable to create a Table with null values in tests.
>>>>
>>>> The code I used is,
>>>>
>>>> def testAggregationWithNull(): Unit = {
>>>>
>>>> val env = ExecutionEnvironment.getExecutionEnvironment
>>>> val table = env.fromElements((123, "a"), (234, "b"), (345, "c"),
>>>> (null, "d")).toTable
>>>>
>>>> val total = table.select('_1.sum).collect().head.productElement(0)
>>>> assertEquals(total, 702)
>>>> }
>>>>
>>>> and the error i get is,
>>>>
>>>> org.apache.flink.api.table.ExpressionException: Invalid expression
>>>> "('_1).sum": Unsupported type GenericType<java.lang.Object> for aggregation
>>>> ('_1).sum. Only numeric data types supported.
>>>> at
>>>> org.apache.flink.api.table.expressions.analysis.TypeCheck.apply(TypeCheck.scala:50)
>>>> at
>>>> org.apache.flink.api.table.expressions.analysis.TypeCheck.apply(TypeCheck.scala:31)
>>>> at
>>>> org.apache.flink.api.table.trees.Analyzer$$anonfun$analyze$1.apply(Analyzer.scala:34)
>>>> at
>>>> org.apache.flink.api.table.trees.Analyzer$$anonfun$analyze$1.apply(Analyzer.scala:31)
>>>> at scala.collection.immutable.List.foreach(List.scala:318)
>>>> at org.apache.flink.api.table.trees.Analyzer.analyze(Analyzer.scala:31)
>>>> at org.apache.flink.api.table.Table$$anonfun$1.apply(Table.scala:59)
>>>> at org.apache.flink.api.table.Table$$anonfun$1.apply(Table.scala:59)
>>>> at
>>>> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
>>>> at
>>>> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
>>>> at
>>>> scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
>>>> at scala.collection.mutable.WrappedArray.foreach(WrappedArray.scala:34)
>>>> at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
>>>> at scala.collection.AbstractTraversable.map(Traversable.scala:105)
>>>> at org.apache.flink.api.table.Table.select(Table.scala:59)
>>>> at
>>>> org.apache.flink.api.scala.table.test.AggregationsITCase.testAggregationWithNull(AggregationsITCase.scala:135)
>>>> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>>>> at
>>>> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
>>>> at
>>>> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
>>>> at
>>>> org.junit.runners.model.FrameworkMethod$1.runReflectiveCall(FrameworkMethod.java:47)
>>>> at
>>>> org.junit.internal.runners.model.ReflectiveCallable.run(ReflectiveCallable.java:12)
>>>> at
>>>> org.junit.runners.model.FrameworkMethod.invokeExplosively(FrameworkMethod.java:44)
>>>> at
>>>> org.junit.internal.runners.statements.InvokeMethod.evaluate(InvokeMethod.java:17)
>>>> at
>>>> org.junit.internal.runners.statements.RunBefores.evaluate(RunBefores.java:26)
>>>> at
>>>> org.junit.internal.runners.statements.RunAfters.evaluate(RunAfters.java:27)
>>>> at org.junit.rules.ExternalResource$1.evaluate(ExternalResource.java:48)
>>>> at org.junit.rules.RunRules.evaluate(RunRules.java:20)
>>>> at org.junit.runners.ParentRunner.runLeaf(ParentRunner.java:271)
>>>> at
>>>> org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:70)
>>>> at
>>>> org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:50)
>>>> at org.junit.runners.ParentRunner$3.run(ParentRunner.java:238)
>>>> at org.junit.runners.ParentRunner$1.schedule(ParentRunner.java:63)
>>>> at org.junit.runners.ParentRunner.runChildren(ParentRunner.java:236)
>>>> at org.junit.runners.ParentRunner.access$000(ParentRunner.java:53)
>>>> at org.junit.runners.ParentRunner$2.evaluate(ParentRunner.java:229)
>>>> at org.junit.runners.ParentRunner.run(ParentRunner.java:309)
>>>> at org.junit.runners.Suite.runChild(Suite.java:127)
>>>> at org.junit.runners.Suite.runChild(Suite.java:26)
>>>> at org.junit.runners.ParentRunner$3.run(ParentRunner.java:238)
>>>> at org.junit.runners.ParentRunner$1.schedule(ParentRunner.java:63)
>>>> at org.junit.runners.ParentRunner.runChildren(ParentRunner.java:236)
>>>> at org.junit.runners.ParentRunner.access$000(ParentRunner.java:53)
>>>> at org.junit.runners.ParentRunner$2.evaluate(ParentRunner.java:229)
>>>> at
>>>> org.junit.internal.runners.statements.RunBefores.evaluate(RunBefores.java:26)
>>>> at
>>>> org.junit.internal.runners.statements.RunAfters.evaluate(RunAfters.java:27)
>>>> at org.junit.runners.ParentRunner.run(ParentRunner.java:309)
>>>> at org.junit.runner.JUnitCore.run(JUnitCore.java:160)
>>>> at
>>>> com.intellij.junit4.JUnit4IdeaTestRunner.startRunnerWithArgs(JUnit4IdeaTestRunner.java:78)
>>>> at
>>>> com.intellij.rt.execution.junit.JUnitStarter.prepareStreamsAndStart(JUnitStarter.java:212)
>>>> at
>>>> com.intellij.rt.execution.junit.JUnitStarter.main(JUnitStarter.java:68)
>>>> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>>>> at
>>>> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
>>>> at com.intellij.rt.execution.application.AppMain.main(AppMain.java:140)
>>>>
>>>>
>>>> The ExecutionEnvironment.fromCollection method also throws an error
>>>> when the collection contains a null.
>>>>
>>>> Could you please point out what I am doing wrong? How do we create a
>>>> Table with null values?
>>>>
>>>> In our application, we load a file and transform each line into a Row
>>>> resulting in a DataSet[Row]. This DataSet[Row] is then converted into
>>>> Table. Should I use the same approach for the test case?
>>>>
>>>>
>>>> Thanks,
>>>> Shiti
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>
>>>> On Sun, Jun 14, 2015 at 4:10 PM, Shiti Saxena <ssaxena....@gmail.com>
>>>> wrote:
>>>>
>>>>> I'll do the fix
>>>>>
>>>>> On Sun, Jun 14, 2015 at 12:42 AM, Aljoscha Krettek <
>>>>> aljos...@apache.org> wrote:
>>>>>
>>>>>> I merged your PR for the RowSerializer. Teaching the aggregators to
>>>>>> deal with null values should be a very simple fix in
>>>>>> ExpressionAggregateFunction.scala. There it is simply always aggregating
>>>>>> the values without checking whether they are null. If you want you can
>>>>>> also
>>>>>> fix that or I can quickly fix it.
>>>>>>
>>>>>> On Thu, 11 Jun 2015 at 10:40 Aljoscha Krettek <aljos...@apache.org>
>>>>>> wrote:
>>>>>>
>>>>>>> Cool, good to hear.
>>>>>>>
>>>>>>> The PojoSerializer already handles null fields. The RowSerializer
>>>>>>> can be modified in pretty much the same way. So you should start by
>>>>>>> looking
>>>>>>> at the copy()/serialize()/deserialize() methods of PojoSerializer and
>>>>>>> then
>>>>>>> modify RowSerializer in a similar way.
>>>>>>>
>>>>>>> You can also send me a private mail if you want more in-depth
>>>>>>> explanations.
>>>>>>>
>>>>>>> On Thu, 11 Jun 2015 at 09:33 Till Rohrmann <trohrm...@apache.org>
>>>>>>> wrote:
>>>>>>>
>>>>>>>> Hi Shiti,
>>>>>>>>
>>>>>>>> here is the issue [1].
>>>>>>>>
>>>>>>>> Cheers,
>>>>>>>> Till
>>>>>>>>
>>>>>>>> [1] https://issues.apache.org/jira/browse/FLINK-2203
>>>>>>>>
>>>>>>>> On Thu, Jun 11, 2015 at 8:42 AM Shiti Saxena <ssaxena....@gmail.com>
>>>>>>>> wrote:
>>>>>>>>
>>>>>>>>> Hi Aljoscha,
>>>>>>>>>
>>>>>>>>> Could you please point me to the JIRA tickets? If you could
>>>>>>>>> provide some guidance on how to resolve these, I will work on them and
>>>>>>>>> raise a pull-request.
>>>>>>>>>
>>>>>>>>> Thanks,
>>>>>>>>> Shiti
>>>>>>>>>
>>>>>>>>> On Thu, Jun 11, 2015 at 11:31 AM, Aljoscha Krettek <
>>>>>>>>> aljos...@apache.org> wrote:
>>>>>>>>>
>>>>>>>>>> Hi,
>>>>>>>>>> yes, I think the problem is that the RowSerializer does not
>>>>>>>>>> support null-values. I think we can add support for this, I will
>>>>>>>>>> open a
>>>>>>>>>> Jira issue.
>>>>>>>>>>
>>>>>>>>>> Another problem I then see is that the aggregations can not
>>>>>>>>>> properly deal with null-values. This would need separate support.
>>>>>>>>>>
>>>>>>>>>> Regards,
>>>>>>>>>> Aljoscha
>>>>>>>>>>
>>>>>>>>>> On Thu, 11 Jun 2015 at 06:41 Shiti Saxena <ssaxena....@gmail.com>
>>>>>>>>>> wrote:
>>>>>>>>>>
>>>>>>>>>>> Hi,
>>>>>>>>>>>
>>>>>>>>>>> In our project, we are using the Flink Table API and are facing
>>>>>>>>>>> the following issues,
>>>>>>>>>>>
>>>>>>>>>>> We load data from a CSV file and create a DataSet[Row]. The CSV
>>>>>>>>>>> file can also have invalid entries in some of the fields which we
>>>>>>>>>>> replace
>>>>>>>>>>> with null when building the DataSet[Row].
>>>>>>>>>>>
>>>>>>>>>>> This DataSet[Row] is later on transformed to Table whenever
>>>>>>>>>>> required and specific operation such as select or aggregate, etc are
>>>>>>>>>>> performed.
>>>>>>>>>>>
>>>>>>>>>>> When a null value is encountered, we get a null pointer
>>>>>>>>>>> exception and the whole job fails. (We can see this by calling
>>>>>>>>>>> collect on
>>>>>>>>>>> the resulting DataSet).
>>>>>>>>>>>
>>>>>>>>>>> The error message is similar to,
>>>>>>>>>>>
>>>>>>>>>>> Job execution failed.
>>>>>>>>>>> org.apache.flink.runtime.client.JobExecutionException: Job
>>>>>>>>>>> execution failed.
>>>>>>>>>>> at
>>>>>>>>>>> org.apache.flink.runtime.jobmanager.JobManager$$anonfun$receiveWithLogMessages$1.applyOrElse(JobManager.scala:315)
>>>>>>>>>>> at
>>>>>>>>>>> scala.runtime.AbstractPartialFunction$mcVL$sp.apply$mcVL$sp(AbstractPartialFunction.scala:33)
>>>>>>>>>>> at
>>>>>>>>>>> scala.runtime.AbstractPartialFunction$mcVL$sp.apply(AbstractPartialFunction.scala:33)
>>>>>>>>>>> at
>>>>>>>>>>> scala.runtime.AbstractPartialFunction$mcVL$sp.apply(AbstractPartialFunction.scala:25)
>>>>>>>>>>> at
>>>>>>>>>>> org.apache.flink.runtime.ActorLogMessages$$anon$1.apply(ActorLogMessages.scala:43)
>>>>>>>>>>> at
>>>>>>>>>>> org.apache.flink.runtime.ActorLogMessages$$anon$1.apply(ActorLogMessages.scala:29)
>>>>>>>>>>> at
>>>>>>>>>>> scala.PartialFunction$class.applyOrElse(PartialFunction.scala:118)
>>>>>>>>>>> at
>>>>>>>>>>> org.apache.flink.runtime.ActorLogMessages$$anon$1.applyOrElse(ActorLogMessages.scala:29)
>>>>>>>>>>> at akka.actor.Actor$class.aroundReceive(Actor.scala:465)
>>>>>>>>>>> at
>>>>>>>>>>> org.apache.flink.runtime.jobmanager.JobManager.aroundReceive(JobManager.scala:94)
>>>>>>>>>>> at akka.actor.ActorCell.receiveMessage(ActorCell.scala:516)
>>>>>>>>>>> at akka.actor.ActorCell.invoke(ActorCell.scala:487)
>>>>>>>>>>> at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:254)
>>>>>>>>>>> at akka.dispatch.Mailbox.run(Mailbox.scala:221)
>>>>>>>>>>> at akka.dispatch.Mailbox.exec(Mailbox.scala:231)
>>>>>>>>>>> at
>>>>>>>>>>> scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
>>>>>>>>>>> at
>>>>>>>>>>> scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
>>>>>>>>>>> at
>>>>>>>>>>> scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
>>>>>>>>>>> at
>>>>>>>>>>> scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
>>>>>>>>>>> Caused by: java.lang.NullPointerException
>>>>>>>>>>> at
>>>>>>>>>>> org.apache.flink.api.common.typeutils.base.IntSerializer.serialize(IntSerializer.java:63)
>>>>>>>>>>> at
>>>>>>>>>>> org.apache.flink.api.common.typeutils.base.IntSerializer.serialize(IntSerializer.java:27)
>>>>>>>>>>> at
>>>>>>>>>>> org.apache.flink.api.table.typeinfo.RowSerializer.serialize(RowSerializer.scala:80)
>>>>>>>>>>> at
>>>>>>>>>>> org.apache.flink.api.table.typeinfo.RowSerializer.serialize(RowSerializer.scala:28)
>>>>>>>>>>> at
>>>>>>>>>>> org.apache.flink.runtime.plugable.SerializationDelegate.write(SerializationDelegate.java:51)
>>>>>>>>>>> at org.apache.flink.runtime.io
>>>>>>>>>>> .network.api.serialization.SpanningRecordSerializer.addRecord(SpanningRecordSerializer.java:76)
>>>>>>>>>>> at org.apache.flink.runtime.io
>>>>>>>>>>> .network.api.writer.RecordWriter.emit(RecordWriter.java:83)
>>>>>>>>>>> at
>>>>>>>>>>> org.apache.flink.runtime.operators.shipping.OutputCollector.collect(OutputCollector.java:65)
>>>>>>>>>>> at
>>>>>>>>>>> org.apache.flink.runtime.operators.chaining.ChainedMapDriver.collect(ChainedMapDriver.java:78)
>>>>>>>>>>> at
>>>>>>>>>>> org.apache.flink.runtime.operators.chaining.ChainedMapDriver.collect(ChainedMapDriver.java:78)
>>>>>>>>>>> at
>>>>>>>>>>> org.apache.flink.runtime.operators.DataSourceTask.invoke(DataSourceTask.java:177)
>>>>>>>>>>> at org.apache.flink.runtime.taskmanager.Task.run(Task.java:559)
>>>>>>>>>>> at java.lang.Thread.run(Thread.java:724)
>>>>>>>>>>>
>>>>>>>>>>> Could this be because the RowSerializer does not support null
>>>>>>>>>>> values? (Similar to Flink-629
>>>>>>>>>>> <https://issues.apache.org/jira/browse/FLINK-629> )
>>>>>>>>>>>
>>>>>>>>>>> Currently, to overcome this issue, we are ignoring all the rows
>>>>>>>>>>> which may have null values. For example, we have a method cleanData
>>>>>>>>>>> defined
>>>>>>>>>>> as,
>>>>>>>>>>>
>>>>>>>>>>> def cleanData(table:Table, relevantColumns:Seq[String]):Table = {
>>>>>>>>>>> val whereClause: String = relevantColumns.map{
>>>>>>>>>>> cName=>
>>>>>>>>>>> s"$cName.isNotNull"
>>>>>>>>>>> }.mkString(" && ")
>>>>>>>>>>>
>>>>>>>>>>> val result :Table =
>>>>>>>>>>> table.select(relevantColumns.mkString(",")).where(whereClause)
>>>>>>>>>>> result
>>>>>>>>>>> }
>>>>>>>>>>>
>>>>>>>>>>> Before operating on any Table, we use this method and then
>>>>>>>>>>> continue with task.
>>>>>>>>>>>
>>>>>>>>>>> Is this the right way to handle this? If not please let me know
>>>>>>>>>>> how to go about it.
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>> Thanks,
>>>>>>>>>>> Shiti
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>
>>>>>
>>>>
>
